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Snowflake SnowPro Advanced: Data Engineer (DEA-C02) Sample Questions:

1. You are designing a system to monitor data access patterns in Snowflake. You want to capture detailed information about all queries executed, including the user, query text, execution time, and any potential data access violations based on security policies. Which of the following approaches, used in combination, would provide the MOST comprehensive and scalable solution for this monitoring requirement? (Select TWO)

A) Create a stored procedure to intercept all SQL commands before execution, log them, and then execute them using 'EXECUTE IMMEDIAT
B) Implement Snowflake's Event Tables and configure them to capture security-related events, such as data access policy violations.
C) Enable query tagging and insert custom tags into each SQL statement indicating sensitive data access. Then, query 'QUERY HISTORY filtering on these tags.
D) Configure the 'SNOWFLAKE database's audit logs and stream them to an external security information and event management (SIEM) system.
E) Enable the 'QUERY_HISTORY view in the 'ACCOUNT_USAGE' schema and periodically query it using a scheduled task.

2. You are building a data pipeline to ingest clickstream data into Snowflake. The raw data is landed in a stage and you are using a Stream on this stage to track new files. The data is then transformed and loaded into a target table 'CLICKSTREAM DATA. However, you notice that sometimes the same files are being processed multiple times, leading to duplicate records in 'CLICKSTREAM DATA. You are using the 'SYSTEM$STREAM HAS DATA' function to check if the stream has data before processing. What are the possible reasons this might be happening, and how can you prevent it? (Select all that apply)

A) The 'SYSTEM$STREAM HAS DATA' function is unreliable and should not be used for production data pipelines. Use 'COUNT( on the stream instead.
B) The auto-ingest notification integration is configured incorrectly, causing duplicate notifications to be sent for the same files. This is particularly applicable when using cloud storage event triggers.
C) The COPY INTO command used to load the files into Snowflake has the 'ON ERROR = CONTINUE option set, allowing it to skip corrupted files, causing subsequent processing to pick them up again.
D) The transformation process is not idempotent. Even with the same input files, it produces different outputs each time it runs.
E) The stream offset is not being advanced correctly after processing the files. Ensure that the files are consumed completely and a DML operation is performed to acknowledge consumption.

3. You are designing a data protection strategy for a Snowflake database. You need to implement dynamic data masking on the 'CREDIT CARD' column in the 'TRANSACTIONS' table. The requirement is that users with the 'FINANCE ADMIN' role should see the full credit card number, while all other users should see only the last four digits. You have the following masking policy:

What is the next step to apply this masking policy to the 'CREDIT CARD' column?

A)

B)

C)

D)

E)

4. You are using the Snowflake REST API to insert data into a table named 'RAW JSON DATA. The JSON data is complex and nested, and you want to efficiently parse and flatten it into a relational structure. You have the following JSON sample:

Which SQL statement, executed after loading the raw JSON using the REST API, is the MOST efficient way to flatten the JSON and extract relevant fields into a new table named 'PURCHASES' with columns like 'EVENT TYPE', 'USER D', 'EMAIL', 'STREET, 'CITY', 'ITEM ID', and 'PRICE'?

A) Option B
B) Option C
C) Option E
D) Option D
E) Option A

5. You are ingesting data from an AWS S3 bucket into a Snowflake table using a COPY INTO statement. The COPY INTO command fails with an error indicating 'Invalid stage location specified'. You have verified that the stage name is correct and the Snowflake user has the necessary privileges to access the stage. However, the error persists. Which of the following are potential causes and solutions for this issue?

A) The S3 bucket policy is not correctly configured to allow Snowflake to assume the IAM role. Review the bucket policy to ensure it grants access to the Snowflake IAM role.
B) The IAM role associated with the Snowflake stage is incorrect or does not have sufficient permissions to access the S3 bucket. Verify the IAM role configuration and permissions.
C) The external stage definition in Snowflake includes an incorrect storage integration. Examine and correct the STORAGE INTEGRATION parameter in the CREATE STAGE statement.
D) The network policy configured in Snowflake is blocking access to the AWS S3 endpoint. Check the network policy rules and ensure they allow outbound traffic to the S3 region.
E) The S3 bucket is encrypted using KMS and the Snowflake integration lacks the necessary key grant. Check the KMS key policy to ensure the storage integration IAM role has decrypt permission.

Solutions: